#include <AdaptiveDMD.h>

Inheritance diagram for CAROM::AdaptiveDMD:

Public Member Functions
	AdaptiveDMD (int dim, double desired_dt=-1.0, std::string rbf="G", std::string interp_method="LS", double closest_rbf_val=0.9, bool alt_output_basis=false, Vector *state_offset=NULL)
	Constructor. More...

	~AdaptiveDMD ()
	Destroy the AdaptiveDMD object.

void	train (double energy_fraction, const Matrix *W0=NULL, double linearity_tol=0.0)

void	train (int k, const Matrix *W0=NULL, double linearity_tol=0.0)

double	getTrueDt () const
	Get the true dt between interpolated snapshots.

const Matrix *	getInterpolatedSnapshots ()
	Get the interpolated snapshot matrix contained within d_interp_snapshots.

Public Member Functions inherited from CAROM::DMD
	DMD (int dim, double dt, bool alt_output_basis=false, Vector *state_offset=NULL)
	Constructor. Basic DMD with uniform time step size. More...

	DMD (std::string base_file_name)
	Constructor. DMD from saved models. More...

virtual	~DMD ()
	Destroy the DMD object.

virtual void	setOffset (Vector *offset_vector, int order)
	Set the offset of a certain order.

virtual void	takeSample (double *u_in, double t)
	Sample the new state, u_in. Any samples in d_snapshots taken at the same or later time will be erased. More...

void	projectInitialCondition (const Vector *init, double t_offset=-1.0)
	Project new initial condition using d_phi. Calculate pinv(phi) x init, or more precisely, (phi* x phi)^{-1} x phi* x init, where phi* is the conjugate transpose. More...

Vector *	predict (double t, int deg=0)
	Predict state given a time. Uses the projected initial condition of the training dataset (the first column). More...

double	getTimeOffset () const
	Get the time offset contained within d_t_offset.

int	getNumSamples () const
	Returns the number of samples taken. More...

int	getDimension () const

const Matrix *	getSnapshotMatrix ()
	Get the snapshot matrix contained within d_snapshots.

virtual void	load (std::string base_file_name)
	Load the object state from a file. More...

void	load (const char *base_file_name)
	Load the object state from a file. More...

virtual void	save (std::string base_file_name)
	Save the object state to a file. More...

void	save (const char *base_file_name)
	Save the object state to a file. More...

void	summary (std::string base_file_name)
	Output the DMD record in CSV files.

Additional Inherited Members
Protected Member Functions inherited from CAROM::DMD
	DMD (int dim, bool alt_output_basis=false, Vector *state_offset=NULL)
	Constructor. Variant of DMD with non-uniform time step size. More...

	DMD (std::vector< std::complex< double >> eigs, Matrix phi_real, Matrix phi_imaginary, int k, double dt, double t_offset, Vector *state_offset)
	Constructor. Specified from DMD components. More...

	DMD ()
	Unimplemented default constructor.

	DMD (const DMD &other)
	Unimplemented copy constructor.

DMD &	operator= (const DMD &rhs)
	Unimplemented assignment operator.

std::pair< Matrix , Matrix >	phiMultEigs (double t, int deg=0)
	Internal function to multiply d_phi with the eigenvalues.

void	constructDMD (const Matrix f_snapshots, int rank, int num_procs, const Matrix W0, double linearity_tol)
	Construct the DMD object.

virtual std::pair< Matrix , Matrix >	computeDMDSnapshotPair (const Matrix *snapshots)
	Returns a pair of pointers to the minus and plus snapshot matrices.

virtual void	computePhi (DMDInternal dmd_internal_obj)
	Compute phi.

virtual std::complex< double >	computeEigExp (std::complex< double > eig, double t)
	Compute the appropriate exponential function when predicting the solution.

virtual void	addOffset (Vector *&result, double t=0.0, int deg=0)
	Add the appropriate offset when predicting the solution.

const Matrix *	createSnapshotMatrix (std::vector< Vector * > snapshots)
	Get the snapshot matrix contained within d_snapshots.

Protected Attributes inherited from CAROM::DMD
int	d_rank
	The rank of the process this object belongs to.

int	d_num_procs
	The number of processors being run on.

int	d_dim
	The total dimension of the sample vector.

double	d_dt = -1.0
	The time step size between samples.

double	d_t_offset
	The time offset of the first sample.

std::vector< Vector * >	d_snapshots
	std::vector holding the snapshots.

std::vector< Vector * >	d_sampled_times
	The stored times of each sample.

Vector *	d_state_offset = NULL
	State offset in snapshot.

bool	d_trained
	Whether the DMD has been trained or not.

bool	d_init_projected
	Whether the initial condition has been projected.

int	d_num_singular_vectors
	The maximum number of singular vectors.

std::vector< double >	d_sv
	std::vector holding the signular values.

double	d_energy_fraction
	The energy fraction used to obtain the DMD modes.

int	d_k
	The number of columns used after obtaining the SVD decomposition.

Matrix *	d_basis = NULL
	The left singular vector basis.

bool	d_alt_output_basis = false
	Whether to use the alternative basis for output, i.e. phi = U^(+)VOmega^(-1)*X.

Matrix *	d_A_tilde = NULL
	A_tilde.

Matrix *	d_phi_real = NULL
	The real part of d_phi.

Matrix *	d_phi_imaginary = NULL
	The imaginary part of d_phi.

Matrix *	d_phi_real_squared_inverse = NULL
	The real part of d_phi_squared_inverse.

Matrix *	d_phi_imaginary_squared_inverse = NULL
	The imaginary part of d_phi_squared_inverse.

Vector *	d_projected_init_real = NULL
	The real part of the projected initial condition.

Vector *	d_projected_init_imaginary = NULL
	The imaginary part of the projected initial condition.

std::vector< std::complex< double > >	d_eigs
	A vector holding the complex eigenvalues of the eigenmodes.

Detailed Description

Class AdaptiveDMD implements the AdaptiveDMD algorithm on a given snapshot matrix.

Definition at line 31 of file AdaptiveDMD.h.

Constructor & Destructor Documentation

◆ AdaptiveDMD()

CAROM::AdaptiveDMD::AdaptiveDMD	(	int	dim,
		double	desired_dt = `-1.0`,
		std::string	rbf = `"G"`,
		std::string	interp_method = `"LS"`,
		double	closest_rbf_val = `0.9`,
		bool	alt_output_basis = `false`,
		Vector *	state_offset = `NULL`
	)

Constructor.

Parameters

[in]	dim	The full-order state dimension.
[in]	desired_dt	The constant step size for uniform interpolation of samples. If set equal to or below 0.0, desired_dt will be set to the median of the different dt's between the samples.
[in]	rbf	The RBF type ("G" == gaussian, "IQ" == inverse quadratic, "IMQ" == inverse multiquadric)
[in]	interp_method	The interpolation method type ("LS" == linear solve, "IDW" == inverse distance weighting, "LP" == lagrangian polynomials)
[in]	closest_rbf_val	The RBF parameter determines the width of influence. Set the RBF value of the nearest two parameter points to a value between 0.0 to 1.0.
[in]	alt_output_basis	Whether to use the alternative basis for output, i.e. phi = U^(+)VOmega^(-1)*X.
[in]	state_offset	The state offset.

Definition at line 22 of file AdaptiveDMD.cpp.

Member Function Documentation

◆ train() [1/2]

void CAROM::AdaptiveDMD::train	(	double	energy_fraction,
		const Matrix *	W0 = `NULL`,
		double	linearity_tol = `0.0`
	)

virtual

Parameters

[in]	energy_fraction	The energy fraction to keep after doing SVD.
[in]	W0	The initial basis to prepend to W.
[in]	linearity_tol	The tolerance for determining whether a column of W is linearly independent with W0.

Reimplemented from CAROM::DMD.

Definition at line 47 of file AdaptiveDMD.cpp.

◆ train() [2/2]

void CAROM::AdaptiveDMD::train	(	int	k,
		const Matrix *	W0 = `NULL`,
		double	linearity_tol = `0.0`
	)

virtual

Parameters

[in]	k	The number of modes (eigenvalues) to keep after doing SVD.
[in]	W0	The initial basis to prepend to W.
[in]	linearity_tol	The tolerance for determining whether a column of W is linearly independent with W0.

Reimplemented from CAROM::DMD.

Definition at line 59 of file AdaptiveDMD.cpp.

The documentation for this class was generated from the following files:

lib/algo/AdaptiveDMD.h
lib/algo/AdaptiveDMD.cpp

Public Member Functions

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ AdaptiveDMD()

Member Function Documentation

◆ train() [1/2]

◆ train() [2/2]